This comprehensive online course in Natural Language Processing (NLP) is designed to equip you with the skills and knowledge required to excel in AI-driven text analysis. Covering everything from the basics of NLP to advanced machine learning applications, this program is ideal for professionals looking to deepen their understanding of language models, text preprocessing, sentiment analysis, and more. With practical exercises and real-world projects, you'll be ready to implement NLP solutions in various industries.
Program Structure
Introduction to Natural Language Processing:
- Overview of NLP and its Applications.
- Key Concepts and Terminologies in NLP.
- Text Preprocessing and Cleaning.
Text Processing and Tokenization:
- Techniques for Text Normalization.
- Tokenization Methods.
- Stemming and Lemmatization.
Sentiment Analysis:
- Basics of Sentiment Analysis.
- Building Sentiment Analysis Models.
- Evaluating Sentiment Analysis Models.
Topic Modeling:
- Introduction to Topic Modeling.
- Latent Dirichlet Allocation (LDA).
- Implementation of Topic Modeling in Python.
Sequence Models:
- Understanding Sequence Data.
- Recurrent Neural Networks (RNN).
- Long Short-Term Memory (LSTM) Networks.
Transformer Models:
- Introduction to Transformer Models.
- Bidirectional Encoder Representations from Transformers (BERT).
- Implementing Transformers for NLP Tasks.
Practical NLP:
- Working with Python and Jupyter Notebooks.
- Using NLTK and spaCy for NLP Tasks.
- Implementing Advanced NLP Models with Hugging Face Transformers.
Participant’s Eligibility
- Senior undergraduates and graduate students in Computer Science and related fields.
- Professionals in IT, data science, and software development looking to enhance their NLP skills.
Program Outcomes
- Develop a solid understanding of NLP principles and techniques.
- Gain proficiency in text preprocessing, tokenization, and sentiment analysis.
- Implement topic modeling, sequence models, and transformer models like BERT.
- Master the use of key NLP libraries such as NLTK, spaCy, and Hugging Face Transformers.
- Apply NLP concepts to real-world projects and scenarios.
- Enhance Python programming skills for advanced NLP tasks.
- Complete practical coding exercises and projects demonstrating NLP expertise.
- Earn a certificate of completion recognized by industry leaders.
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